Showing papers on "Fingerprint recognition published in 2006"

Digital camera identification from sensor pattern noise

Abstract: In this paper, we propose a new method for the problem of digital camera identification from its images based on the sensor's pattern noise. For each camera under investigation, we first determine its reference pattern noise, which serves as a unique identification fingerprint. This is achieved by averaging the noise obtained from multiple images using a denoising filter. To identify the camera from a given image, we consider the reference pattern noise as a spread-spectrum watermark, whose presence in the image is established by using a correlation detector. Experiments on approximately 320 images taken with nine consumer digital cameras are used to estimate false alarm rates and false rejection rates. Additionally, we study how the error rates change with common image processing, such as JPEG compression or gamma correction.

Performance evaluation of fingerprint verification systems

Abstract: This paper is concerned with the performance evaluation of fingerprint verification systems. After an initial classification of biometric testing initiatives, we explore both the theoretical and practical issues related to performance evaluation by presenting the outcome of the recent fingerprint verification competition (FVC2004). FVC2004 was organized by the authors of this work for the purpose of assessing the state-of-the-art in this challenging pattern recognition application and making available a new common benchmark for an unambiguous comparison of fingerprint-based biometric systems. FVC2004 is an independent, strongly supervised evaluation performed at the evaluators' site on evaluators' hardware. This allowed the test to be completely controlled and the computation times of different algorithms to be fairly compared. The experience and feedback received from previous, similar competitions (FVC2000 and FVC2002) allowed us to improve the organization and methodology of FVC2004 and to capture the attention of a significantly higher number of academic and commercial organizations (67 algorithms were submitted for FVC2004). A new, "light" competition category was included to estimate the loss of matching performance caused by imposing computational constraints. This paper discusses data collection and testing protocols, and includes a detailed analysis of the results. We introduce a simple but effective method for comparing algorithms at the score level, allowing us to isolate difficult cases (images) and to study error correlations and algorithm "fusion." The huge amount of information obtained, including a structured classification of the submitted algorithms on the basis of their features, makes it possible to better understand how current fingerprint recognition systems work and to delineate useful research directions for the future.

Securing Fingerprint Template: Fuzzy Vault with Helper Data

Abstract: An important issue gaining attention in biometrics community is the security and privacy of biometric systems: How robust are these systems against attacks? What happens if the biometric template is lost or stolen? Can the privacy of the users be preserved even when a security breach occurs? Among the numerous attacks that can be launched against these systems, protecting the user template that is stored either locally (e.g., on a smart card) or centrally (e.g., on the server) is a major concern. As a possible solution to this problem, a new class of algorithms, termed biometric cryptosystems has been proposed. These systems do not store the original template but only a transformed version of the template within a cryptographic framework. An example of such systems is the fuzzy vault construct proposed by Juels and Sudan. In this construct, the biometric template is converted to a 2D point cloud, containing a secret such as a symmetric encryption key. The operation of the vault requires some "helper" data. In this paper, we present an implementation of the fuzzy fingerprint vault based on orientation field based helper data that is automatically extracted from the fingerprints. We further show that this helper data does not leak any information about fingerprint minutiae, hence complementing the increased user privacy afforded by the fuzzy fingerprint vault. We demonstrate the vault performance on a public domain fingerprint database.

Fake finger detection by skin distortion analysis

Abstract: Attacking fingerprint-based biometric systems by presenting fake fingers at the sensor could be a serious threat for unattended applications. This work introduces a new approach for discriminating fake fingers from real ones, based on the analysis of skin distortion. The user is required to move the finger while pressing it against the scanner surface, thus deliberately exaggerating the skin distortion. Novel techniques for extracting, encoding and comparing skin distortion information are formally defined and systematically evaluated over a test set of real and fake fingers. The proposed approach is privacy friendly and does not require additional expensive hardware besides a fingerprint scanner capable of capturing and delivering frames at proper rate. The experimental results indicate the new approach to be a very promising technique for making fingerprint recognition systems more robust against fake-finger-based spoofing attempts

Cancelable Biometrics: A Case Study in Fingerprints

Abstract: Biometrics offers usability advantages over traditional token and password based authentication schemes, but raises privacy and security concerns. When compromised, credit cards and passwords can be revoked or replaced while biometrics are permanently associated with a user and cannot be replaced. Cancelable biometrics attempt to solve this by constructing revocable biometric templates. We present several constructs for cancelable templates us- ing feature domain transformations and empirically exam- ine their efficacy. We also present a method for accurate registration which is a key step in building cancelable trans- forms. The overall approach has been tested using large databases and our results demonstrate that without losing much accuracy, we can build a large number of cancelable transforms for fingerprints.

System for and method of securing fingerprint biometric systems against fake-finger spoofing

Abstract: A biometric secured system grants a user access to a host system by classifying a fingerprint used to verify or authorize the user to the system as real or fake. The classification is based on a probability that fingerprint image data corresponds to characteristics that reliably identify the finger as real. The system includes a fingerprint sensor for capturing fingerprint image data coupled to a spoof detection module. In one embodiment, the spoof detection module is programmed to determine spoof probability based on a combination of metrics that include, among other metrics, pixel gray level average and the variance of pixels corresponding to a fingerprint ridge, pixel gray level average and the variance of pixels corresponding to a fingerprint valley, density of sweat pores, and density of sweat streaks, to name a few metrics.

Artificial fingerprint recognition by using optical coherence tomography with autocorrelation analysis.

Abstract: Fingerprint recognition is one of the most widely used methods of biometrics. This method relies on the surface topography of a finger and, thus, is potentially vulnerable for spoofing by artificial dummies with embedded fingerprints. In this study, we applied the optical coherence tomography (OCT) technique to distinguish artificial materials commonly used for spoofing fingerprint scanning systems from the real skin. Several artificial fingerprint dummies made from household cement and liquid silicone rubber were prepared and tested using a commercial fingerprint reader and an OCT system. While the artificial fingerprints easily spoofed the commercial fingerprint reader, OCT images revealed the presence of them at all times. We also demonstrated that an autocorrelation analysis of the OCT images could be potentially used in automatic recognition systems.

Fingerprint recognition by combining global structure and local cues

Abstract: As an important feature, orientation field describes the global structure of fingerprints. It provides robust discriminatory information other than traditional widely-used minutiae points. However, there are few works explicitly incorporating this information into fingerprint matching stage, partly due to the difficulty of saving the orientation field in the feature template. In this paper, we propose a novel representation for fingerprints which includes both minutiae and model-based orientation field. Then, fingerprint matching can be done by combining the decisions of the matchers based on the global structure (orientation field) and the local cue (minutiae). We have conducted a set of experiments on large-scale databases and made thorough comparisons with the state-of-the-arts. Extensive experimental results show that combining these local and global discriminative information can largely improve the performance. The proposed system is more robust and accurate than conventional minutiae-based methods, and also better than the previous works which implicitly incorporate the orientation information. In this system, the feature template takes less than 420 bytes, and the feature extraction and matching procedures can be done in about 0.30 s. We also show that the global orientation field is beneficial to the alignment of the fingerprints which are either incomplete or poor-qualitied.

User authentication using biometric information

Abstract: An input unit accepts a fingerprint image of a user. A pre-extraction and categorization unit generates pre-extracted data from the fingerprint image and uses the data to categorize the input fingerprint image into one of multiple groups. A feature extraction unit extracts fingerprint feature data from the fingerprint image by processing methods defined for the respective groups. A feature data matching processing unit matches the fingerprint feature data against fingerprint authentication data registered in a fingerprint authentication database by processing methods defined for the respective groups. An integrated authentication unit authenticates a user with the input fingerprint image based upon a result of matching.

Contoured biometric sensor

Abstract: Disclosed herein is an apparatus and system for fingerprint recognition and hand-print recognition comprising a scanner with a contoured surface, or a scanner the surface of which deforms to allow more fingerprint or hand-print data to be captured, an application specific circuit for conversion of analog data from a captured fingerprint image from an embedded sensor array into a digital image and a fingerprint security application for verification of said digital image against stored fingerprint templates. The scanner array wrap with the embedded scanner array may be placed over the fixture to be scanned, or it may be formed as a part of the fixture that is scanned to authenticate the identity of a person.

Robust biometric image watermarking for fingerprint and face template protection

Abstract: This paper presents a combined DWT and LSB based biometric watermarking algorithm that securely embeds a face template in a fingerprint image. The proposed algorithm is robust to geometric and frequency attacks and protects the integrity of both the face template and the fingerprint image. Experimental results performed on a database of 750 face and 750 fingerprint images show that the algorithm has the advantages of both the existing DWT and LSB based algorithms. A multimodal biometric algorithm is used as a metric to evaluate the combined performance of both face and fingerprint recognition.

The Surround Imager : A multi-camera touchless device to acquire 3D rolled-equivalent fingerprints

Abstract: The Surround Imager , an innovative multi-camera touchless device able to capture rolled-equivalent fingerprints, is here presented for the first time. Due to the lack of contact between the elastic skin of the finger and any rigid surface, the acquired images present no deformation. The multi-camera system acquires different finger views that are combined together to provide a 3D representation of the fingerprint. This new representation leads to a new definition of minutiae bringing new challenges in the field of fingerprint recognition.

Hand Vein Recognition Based on Multi Supplemental Features of Multi-Classifier Fusion Decision

Abstract: As a kind of biometric feature authentication system, hand vein recognition has more merits than others. So it has a vast foreground. In this paper, a new algorithm based on multi supplemental features of multi-classifier fusion decision is proposed. It overcomes the disadvantages of the single feature recognition. Experimental results indicate that the proposed methods can significantly improve the recognition accuracy and reliability compared to the previous hand vein recognition.

An algorithm for distorted fingerprint matching based on local triangle feature set

Abstract: Coping with nonlinear distortions in fingerprint matching is a challenging task. This paper proposes a novel method, a fuzzy feature match (FFM) based on a local triangle feature set to match the deformed fingerprints. The fingerprint is represented by the fuzzy feature set: the local triangle feature set. The similarity between the fuzzy feature set is used to characterize the similarity between fingerprints. A fuzzy similarity measure for two triangles is introduced and extended to construct a similarity vector including the triangle-level similarities for all triangles in two fingerprints. Accordingly, a similarity vector pair is defined to illustrate the similarities between two fingerprints. The FFM method maps the similarity vector pair to a normalized value which quantifies the overall image to image similarity. The proposed algorithm has been evaluated with NIST 24 and FVC2004 fingerprint databases. Experimental results confirm that the proposed FFM based on the local triangle feature set is a reliable and effective algorithm for fingerprint matching with nonlinear distortions.

The surround Imager™: a multi-camera touchless device to acquire 3d rolled-equivalent fingerprints

Abstract: The Surround ImagerTM, an innovative multi-camera touchless device able to capture rolled-equivalent fingerprints, is here presented for the first time Due to the lack of contact between the elastic skin of the finger and any rigid surface, the acquired images present no deformation The multi-camera system acquires different finger views that are combined together to provide a 3D representation of the fingerprint This new representation leads to a new definition of minutiae bringing new challenges in the field of fingerprint recognition

Liveness Detection for Fingerprint Scanners Based on the Statistics of Wavelet Signal Processing

Abstract: Fingerprint scanners can be spoofed by artificial fingers using moldable plastic, clay, Play-Doh, gelatin, silicone rubber materials, etc. Liveness detection is an anti-spoofing method which can detect physiological signs of life from fingerprints to ensure only live fingers can be captured for enrollment or authentication. In this paper, a new method based on the wavelet transform on the ridge signal extracted along the ridge mask is proposed which can detect the perspiration phenomenon using only a single image. Statistical features are extracted for multiresolution scales to discriminate between live and non-live fingers. Based on these features, we use a classification tree to generate the decision rules for the liveness classification. We test this method on the dataset which contains about 58 live, 80 spoof (50 made from Play-Doh and 30 made from gelatin), and 25 cadaver subjects for 3 different scanners. Also, we test this method on a second dataset which contains 33 live and 33 spoof (made from gelatin) subjects. The proposed liveness detection method is purely software based and application of this method can provide anti-spoofing protection for fingerprint scanners.

3D Touchless Fingerprints: Compatibility with Legacy Rolled Images

Abstract: Fingerprints are traditionally captured based on contact of the finger on paper or a platen surface. This often results in partial or degraded images due to improper finger placement, skin deformation, slippage and smearing, or sensor noise from wear and tear of surface coatings. A new generation of touchless live scan devices that generate 3D representation of finger-prints iS appearing in the market. This new sensing technology addresses manye of the problems stated above. However, 3D touchless fingerprint images need to be compatible with the legacy rolled images used in Automated Fingerprint Identification Systems (AFIS). In order to solve this interoperability issue, we propose an unwrapping algorithm that unfolds the 3D fingerprint in such a way that it resembles the effect of virtually rolling the 3D finger on a 2D plane Our preliminary experiments show promising results in obtaining touchless fingerprint images that are of high quality and at the same time compatible with legacy rolled fingerprint images.

Unobtrusive multimodal biometrics for ensuring privacy and information security with personal devices

Abstract: The need for authenticating users of ubiquitous mobile devices is becoming ever more critical with the increasing value of information stored in the devices and of services accessed via them. Passwords and conventional biometrics such as fingerprint recognition offer fairly reliable solutions to this problem, but these methods require explicit user authentication and are used mainly when a mobile device is being switched on. Furthermore, conventional biometrics are sometimes perceived as privacy threats. This paper presents an unobtrusive method of user authentication for mobile devices in the form of recognition of the walking style (gait) and voice of the user while carrying and using the device. While speaker recognition in noisy conditions performs poorly, combined speaker and accelerometer-based gait recognition performs significantly better. In tentative tests with 31 users the Equal Error Rate varied between 2% and 12% depending on noise conditions, typically less than half of the Equal Error Rates of individual modalities.

Unobtrusive multimodal biometrics for ensuring privacy and information security with personal devices

Abstract: The need for authenticating users of ubiquitous mobile devices is becoming ever more critical with the increasing value of information stored in the devices and of services accessed via them. Passwords and conventional biometrics such as fingerprint recognition offer fairly reliable solutions to this problem, but these methods require explicit user authentication and are used mainly when a mobile device is being switched on. Furthermore, conventional biometrics are sometimes perceived as privacy threats. This paper presents an unobtrusive method of user authentication for mobile devices in the form of recognition of the walking style (gait) and voice of the user while carrying and using the device. While speaker recognition in noisy conditions performs poorly, combined speaker and accelerometer-based gait recognition performs significantly better. In tentative tests with 31 users the Equal Error Rate varied between 2% and 12% depending on noise conditions, typically less than half of the Equal Error Rates of individual modalities.

Fingerprint recognition system

Abstract: A method and system of increasing the acceptance rate in fingerprint scans by the application of cascaded selective, plural and sequenced fingerprint recognition rules using a plurality of sensors. The finger is swiped over multiple sensors. A whole fingerprint sample is constructed from the scan of each of the multiple sensors, thereby generating a multiplicity of whole fingerprint samples. Predetermined selective, plural and sequenced fingerprint recognition rules are set for each of the whole fingerprint samples. The sequence of application of the rules is set for the fingerprint recognition. The accuracy level for fingerprint recognition is set. The selective, plural and sequenced fingerprint recognition rules are sequentially applied to match the captured fingerprint image with stored fingerprint templates. The stored fingerprint templates are sequentially filtered until the set accuracy level is achieved.

Preprocessing of a fingerprint image captured with a mobile camera

Abstract: A preprocessing algorithm of a fingerprint image captured with a mobile camera is proposed. Fingerprint images from a mobile camera are different from images from conventional or touch-based sensors such as optical, capacitive, and thermal sensors. For example, images from a mobile camera are colored and the backgrounds or non-finger regions can be very erratic depending on how the image captures time and place. Also, the contrast between the ridges and valleys of images from a mobile camera is lower than that of images from touch-based sensors. Because of these differences between the input images, a new and modified fingerprint preprocessing algorithm is required for fingerprint recognition when using images captured with a mobile camera.

Protecting Fingerprint Data Using Watermarking

Abstract: A motivation for the use of watermarking techniques in biometric systems has been the need to provide increased security to the biometrics data themselves. We introduce an application of wavelet-based watermarking method to hide the fingerprint minutiae data in fingerprint images. The application provides a high security to both hidden data (i.e. fingerprint minutiae) that have to be transmitted and the host image (i.e. fingerprint). The original unmarked fingerprint image is not required to extract the minutiae data. The method is essentially introduced to increase the security of fingerprint minutiae transmission and can also used to protect the original fingerprint image

On the Vulnerability of Fingerprint Verification Systems to Fake Fingerprints Attacks

Abstract: A new method to generate gummy fingers is presented. A medium-size fake fingerprint database is described and two different fingerprint verification systems are evaluated on it. Three different scenarios are considered in the experiments, namely: enrollment and test with real fingerprints, enrollment and test with fake fingerprints, and enrollment with real fingerprints and test with fake fingerprints. Results for an optical and a thermal sweeping sensors are given. Both systems are shown to be vulnerable to direct attacks.

Automatic Image Quality Assessment with Application in Biometrics

Abstract: A method using local features to assess the quality of an image, with demonstration in biometrics, is proposed. Recently, image quality awareness has been found to increase recognition rates and to support decisions in multimodal authentication systems significantly. Nevertheless, automatic quality assessment is still an open issue, especially with regard to general tasks. Indicators of perceptual quality like noise, lack of structure, blur, etc. can be retrieved from the orientation tensor of an image, but there are few studies reporting on this. Here we study the orientation tensor with a set of symmetry descriptors, which can be varied according to the application. Allowed classes of local shapes are generically provided by the user but no training or explicit reference information is required. Experimental results are given for fingerprint. Furthermore, we indicate the applicability of the proposed method to face images.

A study of touchless fingerprint recognition system

Abstract: Fingerprint recognition systems are widely used in the field of biometrics Many existing fingerprint sensors acquire fingerprint images as the user’s fingerprint is contacted on a solid flat sensor Because of this contact, input images from the same finger can be quite different and there are latent fingerprint issues that can lead to forgery and hygienic problems For these reasons, a touchless fingerprint recognition system has been investigated, in which a fingerprint image can be captured without contact While this system can solve the problems which arise through contact of the user’s finger, other challenges emerge, for example, low ridge-valley contrast, and 3D to 2D image mapping In this paper we discuss both the disadvantages and the advantages of touchless fingerprint systems and introduce the hardware and algorithm approach to solve the problems We describe the structure of illuminator and the wavelength of light to acquire a high contrast fingerprint images To solve the problem of 3D to 2D image mapping, we describe the method to remove the strong view difference fingerprint images Experiments show that the touchless fingerprint system has better performance than the conventional touch based system

Biometric information input apparatus

Abstract: The biometric information input apparatus comprises a fingerprint sensor which detects biometric information, and moisture absorbing units and which are arranged adjacent to the fingerprint sensor and absorb moisture. The moisture absorbing units and have a groove structure which generates a capillary phenomenon. The fingerprint sensor is of the sweep type which scans biometric information through relative displacement with the finger, and is formed in parallel with the direction of relative displacement between the groove structure and the finger. The groove structure has a width smaller than the pitch of the ridges of an average fingerprint.

Template Adaptation based Fingerprint Verification

Abstract: This paper proposes a minutiae-based template adaptation algorithm which can be applied after the fingerprint authentication process. The algorithm updates a template by using a query fingerprint, which is successfully verified by the fingerprint matcher as a high quality genuine input. This algorithm generates an updated minutiae set by using not only the minutiae but also local fingerprint quality information and utilizes a successive Bayesian estimation to evaluate the credibility of minutiae and their types. The proposed algorithm updates fingerprint minutiae information in the template as well as appends new minutiae from the query fingerprint. Preliminary experiments show an average 32.7% EER reduction and an even higher matching accuracy improvement at low false accept rates.

Impact of Image Quality on Performance: Comparison of Young and Elderly Fingerprints

Abstract: Performance of fingerprint recognition systems is heavily influenced by the quality of fingerprints provided by the user. Image quality analysis is traditionally performed using local and global structures of fingerprint images like ridge flow, analysis of ridge-valley structures, contrast ratios etc. With large scale deployment of fingerprint recognition in systems like US VISIT program, image quality issues of fingerprint images from extreme age groups becomes even a more important issue. The impact of image quality on performance of fingerprint recognition systems should be a positive one i.e. higher image quality should lead to better overall performance of the system, and removal of lower quality images should improve performance of the system. This research study studied the impact of fingerprint image quality of two different age groups: 18-25, and 62 and above on overall performance using two different matchers. The difference in image quality between the two age groups was analyzed, and then the impact of image quality on performance of fingerprint matchers between the two groups was analyzed. Image quality analysis was performed using NFIQ which is part of NIST Fingerprint Image Software (NFIS). Neurotechnologija VeriFinger and bozorth3 (NFIS) matchers were used to assess overall performance. For the purposes of the research study, overall performance was measured using False Non Matches.

Fingerprint recognition using DCT features

Abstract: A method of fingerprint recognition based on the DCT features of a discrete image is proposed. Its performance is evaluated by the k-nearest neighbour (k-NN) classifier. Experimental results show the achievement of the proposed method in terms of the recognition rate and the low computational effort.